Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images

Detalhes bibliográficos
Autor(a) principal: Silveira, Eduarda Martiniano de Oliveira
Data de Publicação: 2017
Outros Autores: Mello, José Márcio de, Acerbi Júnior, Fausto Weimar, Reis, Aliny Aparecida dos, Withey, Kieran Daniel, Ruiz, Luis Angel
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/30864
Resumo: Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index) was generated in an area of Brazilian amazon tropical forest (1,000 km²). We selected samples (1 x 1 km) from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property) and range (φ-the length scale of the spatial structures of objects) parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA) approaches.
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spelling Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI imagesCaracterizacão da heterogeneidade espacial da paisagem utilizando parâmetros do semivariograma derivados de imagens NDVIRemote sensingGeostatisticsForested areasHuman-modified landscapesSensoriamento remotoGeoestatísticaFlorestasAção antrópicaAssuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index) was generated in an area of Brazilian amazon tropical forest (1,000 km²). We selected samples (1 x 1 km) from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property) and range (φ-the length scale of the spatial structures of objects) parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA) approaches.Assumindo a existência de uma relação entre a heterogeneidade da paisagem e medidas de dependência espacial obtidas de dados de sensoriamento remoto, o objetivo deste estudo foi avaliar o potencial dos parâmetros do semivariograma derivados de imagens de satélite com diferentes resoluções espaciais, para caracterizar áreas cobertas por floresta e áreas sob ação antrópica. Para isso, o NDVI (Índice de Vegetação da Diferença Normalizada) de cada umas das imagens (SPOT 6, Landsat 8 e MODIS Terra) foi gerado em uma área de floresta tropical Amazônica (1.000 km²), onde foram selecionadas amostras (1 x 1 km) de áreas florestadas e áreas antrópicas. A partir destes dados, foram gerados os semivariogramas e extraídos os parâmetros patamar (σ²-variabilidade espacial total) e alcance (φ-distância dentro da qual as amostras apresentam-se estruturadas espacialmente). A análise revelou que a resolução espacial das imagens influencia os parâmetros σ² e φ, apresentando significativo aumento das áreas de florestas para as áreas sob ação antrópica. A maior variação entre estas classes foi obtida com as imagens Landsat 8, indicando estas imagens, com resolução espacial de 30 metros, a mais apropriada para a obtenção dos parâmetros do semivariograma objetivando a caracterização da heterogeneidade espacial da paisagem. Combinando o sensoriamento remoto e técnicas geostatisticas, demonstrou-se que os parâmetros do semivariograma derivados de imagens NDVI podem ser utilizados como um simples indicador de heterogeneidade da paisagem, gerando mapas que permitem aos pesquisadores delinearem com maior eficácia o regime de amostragem. Outras aplicações combinando estas duas técnicas devem ser investigadas, como por exemplo a detecção de mudanças na cobertura do solo e a classificação de imagens utilizando análises orientada a objetos (OBIA).Universidade Federal de Lavras2018-09-28T20:40:16Z2018-09-28T20:40:16Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSILVEIRA, E. M. de O. et al. Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images. Cerne, Lavras, v. 23, n. 4, Oct./Dec. 2017.http://repositorio.ufla.br/jspui/handle/1/30864Cernereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessSilveira, Eduarda Martiniano de OliveiraMello, José Márcio deAcerbi Júnior, Fausto WeimarReis, Aliny Aparecida dosWithey, Kieran DanielRuiz, Luis Angelpor2018-09-28T20:40:17Zoai:localhost:1/30864Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2018-09-28T20:40:17Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
Caracterizacão da heterogeneidade espacial da paisagem utilizando parâmetros do semivariograma derivados de imagens NDVI
title Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
spellingShingle Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
Silveira, Eduarda Martiniano de Oliveira
Remote sensing
Geostatistics
Forested areas
Human-modified landscapes
Sensoriamento remoto
Geoestatística
Florestas
Ação antrópica
title_short Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
title_full Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
title_fullStr Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
title_full_unstemmed Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
title_sort Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images
author Silveira, Eduarda Martiniano de Oliveira
author_facet Silveira, Eduarda Martiniano de Oliveira
Mello, José Márcio de
Acerbi Júnior, Fausto Weimar
Reis, Aliny Aparecida dos
Withey, Kieran Daniel
Ruiz, Luis Angel
author_role author
author2 Mello, José Márcio de
Acerbi Júnior, Fausto Weimar
Reis, Aliny Aparecida dos
Withey, Kieran Daniel
Ruiz, Luis Angel
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Silveira, Eduarda Martiniano de Oliveira
Mello, José Márcio de
Acerbi Júnior, Fausto Weimar
Reis, Aliny Aparecida dos
Withey, Kieran Daniel
Ruiz, Luis Angel
dc.subject.por.fl_str_mv Remote sensing
Geostatistics
Forested areas
Human-modified landscapes
Sensoriamento remoto
Geoestatística
Florestas
Ação antrópica
topic Remote sensing
Geostatistics
Forested areas
Human-modified landscapes
Sensoriamento remoto
Geoestatística
Florestas
Ação antrópica
description Assuming a relationship between landscape heterogeneity and measures of spatial dependence by using remotely sensed data, the aim of this work was to evaluate the potential of semivariogram parameters, derived from satellite images with different spatial resolutions, to characterize landscape spatial heterogeneity of forested and human modified areas. The NDVI (Normalized Difference Vegetation Index) was generated in an area of Brazilian amazon tropical forest (1,000 km²). We selected samples (1 x 1 km) from forested and human modified areas distributed throughout the study area, to generate the semivariogram and extract the sill (σ²-overall spatial variability of the surface property) and range (φ-the length scale of the spatial structures of objects) parameters. The analysis revealed that image spatial resolution influenced the sill and range parameters. The average sill and range values increase from forested to human modified areas and the greatest between-class variation was found for LANDSAT 8 imagery, indicating that this image spatial resolution is the most appropriate for deriving sill and range parameters with the intention of describing landscape spatial heterogeneity. By combining remote sensing and geostatistical techniques, we have shown that the sill and range parameters of semivariograms derived from NDVI images are a simple indicator of landscape heterogeneity and can be used to provide landscape heterogeneity maps to enable researchers to design appropriate sampling regimes. In the future, more applications combining remote sensing and geostatistical features should be further investigated and developed, such as change detection and image classification using object-based image analysis (OBIA) approaches.
publishDate 2017
dc.date.none.fl_str_mv 2017
2018-09-28T20:40:16Z
2018-09-28T20:40:16Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv SILVEIRA, E. M. de O. et al. Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images. Cerne, Lavras, v. 23, n. 4, Oct./Dec. 2017.
http://repositorio.ufla.br/jspui/handle/1/30864
identifier_str_mv SILVEIRA, E. M. de O. et al. Characterizing landscape spatial heterogeneity using semivariogram parameters derived from NDVI images. Cerne, Lavras, v. 23, n. 4, Oct./Dec. 2017.
url http://repositorio.ufla.br/jspui/handle/1/30864
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv Cerne
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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